Artists portray human faces with the Fourier statistics of complex natural scenes

Institute of Anatomy I, School of Medicine, Friedrich Schiller University, Germany.
Network Computation in Neural Systems (Impact Factor: 0.5). 10/2007; 18(3):235-48. DOI: 10.1080/09548980701574496
Source: PubMed

ABSTRACT When artists portray human faces, they generally endow their portraits with properties that render the faces esthetically more pleasing. To obtain insight into the changes introduced by artists, we compared Fourier power spectra in photographs of faces and in portraits by artists. Our analysis was restricted to a large set of monochrome or lightly colored portraits from various Western cultures and revealed a paradoxical result. Although face photographs are not scale-invariant, artists draw human faces with statistical properties that deviate from the face photographs and approximate the scale-invariant, fractal-like properties of complex natural scenes. This result cannot be explained by systematic differences in the complexity of patterns surrounding the faces or by reproduction artifacts. In particular, a moderate change in gamma gradation has little influence on the results. Moreover, the scale-invariant rendering of faces in artists' portraits was found to be independent of cultural variables, such as century of origin or artistic techniques. We suggest that artists have implicit knowledge of image statistics and prefer natural scene statistics (or some other rules associated with them) in their creations. Fractal-like statistics have been demonstrated previously in other forms of visual art and may be a general attribute of esthetic visual stimuli.

Download full-text


Available from: Joachim Denzler, Mar 11, 2015
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In the last decades many neuroscientists have started to investigate the perception of nature and art by the human visual system. Natural scenes lead to an esthetically pleasing perception, therefore scientists have begun to research the reasons to understand the processing principles of the human visual system. @InProceedings{koch_et_al:DSP:2009:1868, author = {Michael Koch and Joachim Denzler and Christoph Redies}, title = {Universal Image Statistics as a Basis for Esthetic Perception}, booktitle = {Computer Vision in Camera Networks for Analyzing Complex Dynamic Natural Scenes}, year = {2009}, editor = {Joachim Denzler and Michael Koch}, publisher = {Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany}, address = {Dagstuhl, Germany}, URL = {}, annote = {Keywords: Esthetic, Aesthetic, PCA, Power Spectrum, Principal Component Analysis}, }
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: An emerging body of research suggests that artists consistently seek modes of representation that are efficiently processed by the human visual system, and that these shared properties could leave statistical signatures. In earlier work, we showed evidence that perceived similarity of representational art could be predicted using intensity statistics to which the early visual system is attuned, though semantic content was also found to be an important factor. Here we report two studies that examine the visual perception of similarity. We test a collection of non-representational art, which we argue possesses useful statistical and semantic properties, in terms of the relationship between image statistics and basic perceptual responses. We find two simple statistics-both expressed as single values-that predict nearly a third of the overall variance in similarity judgments of abstract art. An efficient visual system could make a quick and reasonable guess as to the relationship of a given image to others (i.e., its context) by extracting these basic statistics early in the visual stream, and this may hold for natural scenes as well as art. But a major component of many types of art is representational content. In a second study, we present findings related to efficient representation of natural scene luminances in landscapes by a well-known painter. We show empirically that elements of contemporary approaches to high-dynamic range tone-mapping-which are themselves deeply rooted in an understanding of early visual system coding-are present in the way Vincent Van Gogh transforms scene luminances into painting luminances. We argue that global tone mapping functions are a useful descriptor of an artist's perceptual goals with respect to global illumination and we present evidence that mapping the scene to a painting with different implied lighting properties produces a less efficient mapping. Together, these studies suggest that statistical regularities in art can shed light on visual processing.
    Human Vision and Electronic Imaging XIV - part of the IS&T-SPIE Electronic Imaging Symposium, San Jose, CA, USA, January 19-22, 2009, Proceedings; 01/2009
Show more